Climate feedbacks, including Planck, surface albedo, water vapor-lapse rate (WVLR) and cloud feedbacks, determine how much surface temperatures will eventually warm to balance anthropogenic radiative forcing. Climate feedbacks remain difficult to constrain directly from temporal variation in observed surface warming and radiation budgets due to the short historical record and low signal-to-noise ratio, with only order 1{degree sign}C historic rise in surface temperatures and high uncertainty in aerosol radiative forcing. This study presents a new method to analyze climate feedbacks from observations by empirically fitting simplified reduced-physics relations for outgoing radiation at the top of the atmosphere (TOA) to observed spatial variation in climate properties and radiation budgets. Spatial variations in TOA outgoing radiation are dominated by the dependence on surface temperature: around 85% of the spatial variation in clear sky albedo, and 78% of spatial variation in clear sky TOA outgoing longwave radiation, is functionally explained by variation in surface temperatures. These simplified and observationally constrained relations are then differentiated with respect to spatial contrasts in surface temperature to reveal the Planck, surface albedo (λ_abedo) and WVLR (λ_WVLR) climate feedbacks spatially for both clear sky and all sky conditions. The resulting global all sky climate feedback values are λ_WVLR=1.30 (1.20 to 1.40 at 66%) Wm-2K-1, and λ_abedo=0.60 (0.53 to 0.66) Wm-2 for the 2003-2023 period reducing to 0.32 (0.28 to 0.35) Wm-2K-1 under 4{degree sign}C warming after cryosphere retreat. Our findings agree well with complex Earth system model evaluations based on temporal climate perturbations, and our approach is complementary.

Slow climate feedbacks are currently underrepresented in model assessments of climate sensitivity and their magnitudes are still poorly constrained. We combine a recently published record of Earth’s Energy Imbalance (EEI) with existing reconstructions of temperature, atmospheric composition, and sea level to estimate both the magnitude and timescale of the ice sheet-albedo feedback since the Last Glacial Maximum. This facilitates the first opportunity to quantify this feedback over the most recent deglaciation using a purely proxy data-driven approach, without the need for simulated reconstructions. We find the ice sheet-albedo feedback to be amplifying, reaching an equilibrium magnitude of 0.55 Wm-2K-1, with a 66% confidence interval of 0.45 - 0.63 Wm-2K-1. The timescale to equilibrium is estimated as 3.6Kyrs (66% confidence: 1.9 - 5.5Kyrs). These results provide new evidence for the timescale and magnitude of the amplifying ice sheet-albedo feedback that will continue to drive anthropogenic warming for millennia to come.

Climate feedbacks determine how much surface temperatures will eventually warm to balance anthropogenic radiative forcing, but remain difficult to constrain. The climate feedback due to some process X is defined as the partial derivative of outgoing radiation at the top of the atmosphere with respect to surface temperature following a change in X, λX=-∂Rout/TS|X, with total climate feedback a summation from all processes, λtotal=∑λX. Standard approaches evaluate climate feedbacks from finite temporal changes in surface temperatures and outgoing radiation, following observed or simulated perturbations to climate state. However, this introduces significant linear combination error (λtotal≠∑λX) when the applied perturbation is large enough to achieve a good signal-to-noise ratio. This study presents a new semi-empirical evaluation of non-cloud climate feedbacks, constrained instead by spatial variation in outgoing radiation and climate state. First, we observationally constrain functional relations for outgoing radiation over ocean and land in terms of surface temperature, pressure, relative humidity, the height of the tropopause, fractional clound amount and latitude. Then, these functional relations are differentiated with respect to surface temperature to calculate the climate feedbacks for infinitesimal perturbation, eliminating linear combination error at high signal-to-noise ratio. We find, when combined with a recent cloud feedback estimate, a present-day total climate feedback of -0.99 (-0.75 to -1.22 at 66% range) Wm-2K-1. Our method is independent of temporal variation approaches to evaluate climate feedback allowing Bayesian combination to further reduce uncertainty.

Oxygen isotopes in marine sediments (δ 18 O) are used to reconstruct Earth’s past temperature and reveal a generally cooling climate over the Cenozoic (66Ma-present). This trend is punctuated by large multimillenial thermal extreme events, most notably the Paleocene-Eocene Thermal Maximum (56Ma). We show that the distribution of these thermal extremes is excellently captured by the generalized extreme value distribution. This then motivates its use to investigate the state-dependence of these extremes. The distribution’s shape, captured by the shape parameter ξ, changes consistently with baseline δ 18 O values, such that large thermal extremes (>3 standard deviations) are far more likely in warmer climate states. We project that anthropogenic warming has the potential to return the baseline climate state to one where large thermal extremes are substantially more likely. Short title: Thermal extreme state-dependence 66-0Ma One-Sentence Summary: Warmer baseline climate states are associated with more extreme multimillenial warming events over the past 66 million years.